Different resolution of input images about flownet2-docker

[nikolausmayer]

You're right, once initialized the network is fixed to one exact resolution. We need image widths and heights that are multiples of 64, and so we have to setup upsampling and downsampling layers before/after the core network. The flow output even needs special treatment.

I can think of 4 different workflows here:

• (easiest, slowest) Call the docker script for each image pair individually.
• (still easy, a little faster) Change the Python script which the docker command executes. Currently the script initializes the network once, but it should not be too hard to rewrite it such that the network is reinitialized whenever the input size changes. This could be fast if your input list is sorted by image size, and if many input images share a common size (as should be the case in your example).
• (still easy, also faster) What you propose: Sort the inputs by sizes and create lists for each size class. If the whole docker overhead is not too bad, this might be as good as the previous option.
• (difficult, but fast) Actually rewrite the network layers such that they can deal with dynamic input sizes. I would ... not recommend this :P

[meegoStar]

Great! Thanks for your reply. I would try the 2nd method first.
The 4th would be too much work for me now :D
Big thanks again!